Overview

Brought to you by YData

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory390.8 KiB
Average record size in memory40.0 B

Variable types

Numeric4
Categorical1

Alerts

Sleep_Duration_Hours has unique values Unique

Reproduction

Analysis started2025-03-19 05:28:54.238032
Analysis finished2025-03-19 05:29:22.714750
Duration28.48 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

Heart_Rate_BPM
Real number (ℝ)

Distinct60
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.822
Minimum60
Maximum119
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-03-19T14:29:22.799712image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile63
Q175
median90
Q3105
95-th percentile117
Maximum119
Range59
Interquartile range (IQR)30

Descriptive statistics

Standard deviation17.309144
Coefficient of variation (CV)0.19270495
Kurtosis-1.196922
Mean89.822
Median Absolute Deviation (MAD)15
Skewness-0.0073183543
Sum898220
Variance299.60648
MonotonicityNot monotonic
2025-03-19T14:29:22.946618image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
113 197
 
2.0%
106 193
 
1.9%
85 193
 
1.9%
104 192
 
1.9%
108 190
 
1.9%
114 189
 
1.9%
82 188
 
1.9%
76 186
 
1.9%
87 184
 
1.8%
118 183
 
1.8%
Other values (50) 8105
81.0%
ValueCountFrequency (%)
60 156
1.6%
61 161
1.6%
62 160
1.6%
63 173
1.7%
64 152
1.5%
65 164
1.6%
66 139
1.4%
67 172
1.7%
68 152
1.5%
69 151
1.5%
ValueCountFrequency (%)
119 173
1.7%
118 183
1.8%
117 175
1.8%
116 172
1.7%
115 161
1.6%
114 189
1.9%
113 197
2.0%
112 158
1.6%
111 159
1.6%
110 166
1.7%

Sleep_Duration_Hours
Real number (ℝ)

Unique 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.9784946
Minimum4.000317
Maximum9.9988309
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-03-19T14:29:23.084540image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum4.000317
5-th percentile4.2995162
Q15.4748091
median6.9516052
Q38.4924012
95-th percentile9.6859343
Maximum9.9988309
Range5.9985139
Interquartile range (IQR)3.0175921

Descriptive statistics

Standard deviation1.7308344
Coefficient of variation (CV)0.24802404
Kurtosis-1.1954725
Mean6.9784946
Median Absolute Deviation (MAD)1.5038231
Skewness0.024651856
Sum69784.946
Variance2.9957878
MonotonicityNot monotonic
2025-03-19T14:29:23.208469image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.696414262 1
 
< 0.1%
7.516663215 1
 
< 0.1%
8.543833572 1
 
< 0.1%
5.398883822 1
 
< 0.1%
4.12983595 1
 
< 0.1%
9.029055524 1
 
< 0.1%
5.027695818 1
 
< 0.1%
4.074496535 1
 
< 0.1%
4.973684946 1
 
< 0.1%
8.192361542 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
4.000316962 1
< 0.1%
4.000946467 1
< 0.1%
4.001445247 1
< 0.1%
4.001446028 1
< 0.1%
4.001457607 1
< 0.1%
4.002409264 1
< 0.1%
4.002461737 1
< 0.1%
4.003325108 1
< 0.1%
4.004301152 1
< 0.1%
4.004737067 1
< 0.1%
ValueCountFrequency (%)
9.998830865 1
< 0.1%
9.998039231 1
< 0.1%
9.997031138 1
< 0.1%
9.996764086 1
< 0.1%
9.996754403 1
< 0.1%
9.996101803 1
< 0.1%
9.996010737 1
< 0.1%
9.995243794 1
< 0.1%
9.993428199 1
< 0.1%
9.993068963 1
< 0.1%

Physical_Activity_Steps
Real number (ℝ)

Distinct7130
Distinct (%)71.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8061.812
Minimum1000
Maximum14998
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-03-19T14:29:23.345400image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1707.95
Q14468.75
median8116
Q311617.25
95-th percentile14357
Maximum14998
Range13998
Interquartile range (IQR)7148.5

Descriptive statistics

Standard deviation4067.1181
Coefficient of variation (CV)0.50449181
Kurtosis-1.2093453
Mean8061.812
Median Absolute Deviation (MAD)3569.5
Skewness-0.017008051
Sum80618120
Variance16541450
MonotonicityNot monotonic
2025-03-19T14:29:23.483312image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4726 5
 
0.1%
8050 5
 
0.1%
1201 5
 
0.1%
14031 5
 
0.1%
9294 5
 
0.1%
2654 5
 
0.1%
5834 5
 
0.1%
6566 5
 
0.1%
9353 5
 
0.1%
2634 5
 
0.1%
Other values (7120) 9950
99.5%
ValueCountFrequency (%)
1000 1
 
< 0.1%
1001 1
 
< 0.1%
1002 1
 
< 0.1%
1003 2
< 0.1%
1008 1
 
< 0.1%
1012 2
< 0.1%
1014 2
< 0.1%
1016 4
< 0.1%
1022 1
 
< 0.1%
1024 1
 
< 0.1%
ValueCountFrequency (%)
14998 1
 
< 0.1%
14997 1
 
< 0.1%
14996 1
 
< 0.1%
14992 1
 
< 0.1%
14991 1
 
< 0.1%
14990 1
 
< 0.1%
14989 3
< 0.1%
14987 1
 
< 0.1%
14986 2
< 0.1%
14982 3
< 0.1%

Mood_Rating
Real number (ℝ)

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0651
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-03-19T14:29:23.583264image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q37
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.5625219
Coefficient of variation (CV)0.50591734
Kurtosis-1.2027078
Mean5.0651
Median Absolute Deviation (MAD)2
Skewness-0.030037733
Sum50651
Variance6.5665186
MonotonicityNot monotonic
2025-03-19T14:29:23.668216image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
5 1178
11.8%
9 1145
11.5%
6 1139
11.4%
7 1134
11.3%
3 1123
11.2%
8 1105
11.1%
4 1091
10.9%
1 1059
10.6%
2 1026
10.3%
ValueCountFrequency (%)
1 1059
10.6%
2 1026
10.3%
3 1123
11.2%
4 1091
10.9%
5 1178
11.8%
6 1139
11.4%
7 1134
11.3%
8 1105
11.1%
9 1145
11.5%
ValueCountFrequency (%)
9 1145
11.5%
8 1105
11.1%
7 1134
11.3%
6 1139
11.4%
5 1178
11.8%
4 1091
10.9%
3 1123
11.2%
2 1026
10.3%
1 1059
10.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size566.5 KiB
1
5157 
0
4843 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters10000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
1 5157
51.6%
0 4843
48.4%

Length

2025-03-19T14:29:23.767159image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-19T14:29:23.825117image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
ValueCountFrequency (%)
1 5157
51.6%
0 4843
48.4%

Most occurring characters

ValueCountFrequency (%)
1 5157
51.6%
0 4843
48.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 5157
51.6%
0 4843
48.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 5157
51.6%
0 4843
48.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 5157
51.6%
0 4843
48.4%

Interactions

2025-03-19T14:29:22.064133image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-19T14:28:54.363961image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-19T14:29:21.190623image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-19T14:29:21.644364image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-19T14:29:22.167074image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-19T14:29:20.756883image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-19T14:29:21.304557image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-19T14:29:21.743306image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-19T14:29:22.295990image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-19T14:29:20.874805image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-19T14:29:21.422490image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-19T14:29:21.849246image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-19T14:29:22.435912image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-19T14:29:21.042708image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-19T14:29:21.528439image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-19T14:29:21.957187image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Correlations

2025-03-19T14:29:23.881096image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Heart_Rate_BPMMental_Health_ConditionMood_RatingPhysical_Activity_StepsSleep_Duration_Hours
Heart_Rate_BPM1.0000.265-0.006-0.003-0.024
Mental_Health_Condition0.2651.0000.0160.0000.315
Mood_Rating-0.0060.0161.0000.0030.003
Physical_Activity_Steps-0.0030.0000.0031.000-0.008
Sleep_Duration_Hours-0.0240.3150.003-0.0081.000

Missing values

2025-03-19T14:29:22.578829image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-19T14:29:22.664781image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Heart_Rate_BPMSleep_Duration_HoursPhysical_Activity_StepsMood_RatingMental_Health_Condition
0987.431376051
11119.461145590
2884.04917481
3748.861261211
41029.69392390
5674.551244651
6804.97423991
7989.76486590
81177.23922930
9784.091089081
Heart_Rate_BPMSleep_Duration_HoursPhysical_Activity_StepsMood_RatingMental_Health_Condition
99901045.011027461
9991939.86788350
9992806.931369450
99931154.35251781
99941149.62584610
99951077.521108781
9996828.20457970
9997657.151182510
99981109.011417591
99991124.20337940